code: def get_callbacks(steps_per_epoch, learning_rate_schedule_fn=None):
      """Returns common callbacks."""
      time_callback = keras_utils.TimeHistory(
          FLAGS.batch_size, FLAGS.log_steps
      )
      callbacks = [time_callback]
  
      if not FLAGS.use_tensor_lr and learning_rate_schedule_fn:
          lr_callback = LearningRateBatchScheduler(
              learning_rate_schedule_fn,
              batch_size=FLAGS.batch_size,
              steps_per_epoch=steps_per_epoch,
          )
          callbacks.append(lr_callback)
  
      if FLAGS.enable_tensorboard:
          tensorboard_callback = tf.keras.callbacks.TensorBoard(
              log_dir=FLAGS.model_dir
          )
          callbacks.append(tensorboard_callback)
  
      if FLAGS.profile_steps:
          profiler_callback = keras_utils.get_profiler_callback(
              FLAGS.model_dir,
              FLAGS.profile_steps,
              FLAGS.enable_tensorboard,
              steps_per_epoch,
          )
          callbacks.append(profiler_callback)
  
      return callbacks
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  import numpy
  import tensorflow
  from tensorflow.python.keras.optimizer_v2 import gradient_descent
  from utils.flags import core
  from utils.misc import keras_utils
label_desc: Use image node_id 3 for calling a global function with example usage: get_callbacks(steps_per_epoch, learning_rate_schedule_fn) and returns: callbacks